UC4 APPLICATION: DRIVERS AND CONSEQUENCES OF b-CELL DNA DAMAGE IN DIABETES Abstract: The prevalence of Diabetes Mellitus has reached epidemic proportions world-wide, and is predicted to increase rapidly in the years to come, putting a tremendous strain on health care budgets in both developed and developing countries. There are two major forms of diabetes and both are associated with decreased beta-cell mass. Exciting recent data have provided evidence that metabolic stress is associated with DNA double strand breaks in multiple models of impaired glycemia. Based on our exciting preliminary data, we propose to develop novel technologies further to specifically determine the accumulated mutation load, as well as physiological responses to genomic stress in human beta- cells, all at the single cell level. In Aim 1, we will determine the molecular mechanisms that cause b- cell DNA damage in diabetes, based on our hypothesis that metabolic and/or inflammatory insults and abortive replication attempts result in formation of double-strand breaks in b-cells, potentially in discrete locations. To this end, we will perform genome-wide CHIP-Seq experiments with antibodies against the DNA damage response proteins 53BP1 and gH2AX, as well as the BLISS method to reveal the location of actual DNA breaks at a single-base resolution in healthy and metabolically- stressed b-cells from mice and humans. In Aim 2, we will analyze the cumulative mutation load of human b-cells in diabetes, based on our hypothesis that metabolic insults and abortive replication attempts result in the accumulation of somatic mutations in b-cells, contributing to their loss of function and possibly to immunogenicity in diabetes. To accomplish this goal, we will determine the cumulative mutation load of stressed b-cells using single cell exome-, RNA-, and ATACseq analysis. To accomplish these aims, we will use cutting-edge and emerging technologies that are already established in our laboratories. We have assembled an outstanding team of scientist with complementary expertise, ranging from human islet transplantation to computational biology, to assemble an atlas of the human endocrine pancreas in health and disease at the single cell level. These datasets and technologies promise to greatly increase our understanding of the human beta- cell in health and disease.